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FAQ

1. How is Prodia different from traditional BI?​

Traditional BI is strong at fixed dashboards and reports. Prodia emphasizes conversational entry, manufacturing-oriented analysis, and diagnostic closed loops.

2. Does Prodia replace AI SCADA or other execution systems?​

No. Prodia works best as an intelligent analysis and coordination layer above existing systems.

3. Why do teams still need Prodia if they already have many reports?​

Because the gap is usually not the number of reports. The gap is the ability to ask questions quickly, follow up, diagnose, and move toward action.

4. What data sources can Prodia work with?​

Typical sources include equipment data, AI SCADA, MES, databases, and other business systems. The actual scope depends on project boundaries.

5. Is AI SCADA mandatory?​

No. Prodia can be planned around the systems already in place. The depth of supported business scenarios depends on the breadth and quality of accessible data.

6. Does Prodia support private deployment?​

Yes. Private and intranet deployment are common for industrial users.

7. How does Prodia improve trustworthiness of AI results?​

Prodia relies on governed business tools, unified metric definitions, clarification before analysis, and knowledge enhancement rather than pure free-form generation.

8. What are the best pilot scenarios?​

Typical first-pilot scenarios include:

  • daily production review
  • OEE / quality root cause analysis
  • takt bottleneck or fault analysis

Yes. Its goal is not only to return a result, but also to suggest what to check next, what to focus on, and what actions may be appropriate.

10. Where is the value most visible?​

Mainly in three areas:

  • shortening analysis and decision time
  • improving exception handling efficiency
  • preserving experience as reusable operational capability

11. What is the best way to categorize Prodia as a product?​

The best framing is:

a standalone but integrable intelligent insight and diagnostic product evolving toward an agent-native platform for industrial operations

12. How would you explain Prodia in one sentence?​

Prodia helps industrial teams get data, reasons, and next-step guidance directly around business questions instead of switching between many systems and reports.

13. Why does Prodia sometimes ask clarifying questions first?​

Because the same sentence in manufacturing may imply different objects, time definitions, or analytical grains. Clarification reduces misunderstanding and keeps results consistent.

14. What kinds of questions fit Prodia best?​

Three types usually fit best:

  • questions about output, quality, OEE, takt, fault, and comparison
  • diagnosis questions around fluctuation, bottlenecks, and cause tracking
  • decision-support questions about what to investigate next and what actions to prioritize

15. Is Prodia’s Agent just one LLM?​

From the user’s perspective it may look like one unified agent. Internally it behaves more like a capability system that routes across analytics, knowledge, and orchestration paths depending on the problem.

16. Why does the same question need object and metric alignment in different factories?​

Because line structure, naming, metric definitions, and business boundaries vary from site to site. Those semantics must be aligned before conversational analytics can be reliable on site.

17. Will Prodia let the Agent access all underlying data arbitrarily?​

No. Prodia emphasizes analysis within governed business capabilities, permission boundaries, and controlled outputs.

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